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DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Ponderomotive force driven density modifications parallel to B on the LAPD

The ponderomotive force has previously been identified as a possible driver of observed density modifications close to radio frequency actuators during operation. This nonlinear force redistributes density in regions of gradients in the magnitude of an oscillating electric field and describes the influence of the fast time scale RF wave dynamics on slow time scale plasma transport. Depletion of the saturation current (a proxy for the density) measured at the Large Plasma Device (LAPD) was 30–35% during ion cyclotron range of frequencies operation. A coupled 1D plasma transport and cold plasma frequency domain wave solver was developed to self-consistently describe ponderomotive effects and was used to compare with results obtained from the LAPD experiment. The scaled current density driver for the wave model yielded an RF B field in close agreement with two components of the experimental data. However, the 1D parallel model did not accurately reproduce the amplitude or spatial distribution observed in experimental measurements of By. Within the limitations of the 1D model, initial simulation results showed that the ponderomotive force depleted up to 8% for high power (1 MW) and around 1% for the experimental power of 120 kW. This could suggest that the ponderomotive force is not the main driver of density modification for the LAPD experiments presented in this paper. Higher fidelity tools of at least 2D will be required to give a more realistic description of the RF E fields and the effect of the ponderomotive force on the LAPD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2004

Solving Large Problems Quickly: Progress in 2001-2003

This document describes the progress we have made and the lessons we have learned in 2001 through 2003 under the NASA grant entitled "Solving Important Problems Faster". The long-term goal of this research is to accelerate large, irregular scientific applications which have enormous data sets and which are difficult to parallelize. To accomplish this goal, we are exploring two complementary techniques: (i) using compiler-inserted prefetching to automatically hide the I/O latency of accessing these large data sets from disk; and (ii) using thread-level data speculation to enable the optimistic parallelization of applications despite uncertainty as to whether data dependences exist between the resulting threads which would normally make them unsafe to execute in parallel. Overall, we made significant progress in 2001 through 2003, and the project has gone well.

Mowry, Todd C.↗

DOE OSTI2016

PolyCheck: Dynamic Verification of Iteration Space Transformations on Affine Programs

High-level compiler transformations, especially loop transformations, are widely recognized as critical optimizations to restructure programs to improve data locality and expose parallelism. Guaranteeing the correctness of program transformations is essential, and to date three main approaches have been developed: proof of equivalence of affine programs, matching the execution traces of programs, and checking bit-by-bit equivalence of the outputs of the programs. Each technique suffers from limitations in either the kind of transformations supported, space complexity, or the sensitivity to the testing dataset. In this paper, we take a novel approach addressing all three limitations to provide an automatic bug checker to verify any iteration reordering transformations on affine programs, including non-affine transformations, with space consumption proportional to the original program data, and robust to arbitrary datasets of a given size. We achieve this by exploiting the structure of affine program control- and data-flow to generate at compile-time lightweight checker code to be executed within the transformed program. Experimental results assess the correctness and effectiveness of our method, and its increased coverage over previous approaches.

affine programs↗

NASA NTRS2020

Impact Testing of Inconel 718 for Material Impact Model Development

One of the difficulties with developing and verifying accurate impact models is that parameters such as high strain-rate material properties, failure modes, static properties, and impact test measurements are often obtained from a variety of different sources using different materials, with little control over consistency among the different sources. In addition, there is often a lack of quantitative measurements in impact tests to which the models can be compared. To alleviate some of these problems, a project is underway to develop a consistent set of material property, impact test data, and failure analysis for a variety of aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the Federal Aviation Administration (FAA) William J. Hughes Technical Center. Unique features of this set of data are that all material property and impact test data are obtained using traceable material, the test methods and procedures are extensively documented, and all of the raw data is available. Four parallel efforts are currently underway. The Ohio State University conducts both measurement of material deformation and failure response over a wide range of strain rates and temperatures and failure analysis of material property specimens and impact test articles. The George Mason University conducts the development of improved numerical modeling techniques for deformation and failure. Glenn conducts the impact testing of flat panels and substructures. This report describes impact testing performed on Inconel 718 sheet and plate samples of different thicknesses with different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

J Michael Pereira↗

DOE OSTI2017

A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark

We investigate the performance and scalability of the randomized CX low-rank matrix factorization and demonstrate its applicability through the analysis of a 1TB mass spectrometry imaging (MSI) dataset, using Apache Spark on an Amazon EC2 cluster, a Cray XC40 system, and an experimental Cray cluster. We implemented this factorization both as a parallelized C implementation with hand-tuned optimizations and in Scala using the Apache Spark high-level cluster computing framework. We obtained consistent performance across the three platforms: using Spark we were able to process the 1TB size dataset in under 30 minutes with 960 cores on all systems, with the fastest times obtained on the experimental Cray cluster. In comparison, the C implementation was 21X faster on the Amazon EC2 system, due to careful cache optimizations, bandwidth-friendly access of matrices and vector computation using SIMD units. We report these results and their implications on the hardware and software issues arising in supporting data-centric workloads in parallel and distributed environments.

Gittens, Alex↗

NASA NTRS1999

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.

Oliker, Leonid↗

NASA NTRS2013

Impact Testing of Aluminum 2024 and Titanium 6Al-4V for Material Model Development

One of the difficulties with developing and verifying accurate impact models is that parameters such as high strain rate material properties, failure modes, static properties, and impact test measurements are often obtained from a variety of different sources using different materials, with little control over consistency among the different sources. In addition there is often a lack of quantitative measurements in impact tests to which the models can be compared. To alleviate some of these problems, a project is underway to develop a consistent set of material property, impact test data and failure analysis for a variety of aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the FAA William J. Hughes Technical Center. Unique features of this set of data are that all material property data and impact test data are obtained using identical material, the test methods and procedures are extensively documented and all of the raw data is available. Four parallel efforts are currently underway: Measurement of material deformation and failure response over a wide range of strain rates and temperatures and failure analysis of material property specimens and impact test articles conducted by The Ohio State University; development of improved numerical modeling techniques for deformation and failure conducted by The George Washington University; impact testing of flat panels and substructures conducted by NASA Glenn Research Center. This report describes impact testing which has been done on aluminum (Al) 2024 and titanium (Ti) 6Al-4vanadium (V) sheet and plate samples of different thicknesses and with different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

Pereira, J. Michael↗

DOE OSTI2022

Toward designing effective exascale scientific computing workflows: experiences and best practices

Many fields within scientific computing have embraced advances in big-data analysis and machine learning, which often requires the deployment of large, distributed and complicated workflows that may combine training neural networks, performing simulations, running inference, and performing database queries and data analysis in asynchronous, parallel and pipelined execution frameworks. Such a shift has brought into focus the need for scalable, efficient workflow management solutions with reproducibility, error and provenance handling, traceability, and checkpoint-restart capabilities, among other needs. Here, we discuss challenges and best-practices for deploying exascale-generation computational science workflows on resources at the Oak Ridge Leadership Computing Facility (OLCF). We present our experiences with large-scale deployment of distributed workflows on the Summit supercomputer, including for bioinformatics and computational biophysics, materials science, and deep learning model optimization. We also present problems and solutions created by working within a Python-centric software base on traditional HPC systems, and discuss steps that will be required before the convergence of HPC, AI, and data science can be fully realized. Our results point to a wealth of exciting new possibilities for harnessing this convergence to tackle new scientific challenges.

Coletti, Mark↗

NASA NTRS1989

Unsteady interaction of a rotor with a vortex

The unsteady, three-dimensional flow field of a helicopter rotor blade encountering a passing vortex is calculated by solving the Euler/thin layer Navier-Stokes equations by a finite-difference numerical procedure. A prescribed vortex method is adopted to preserve the structure of the interacting vortex. The cases considered for computation correspond to the experimental model rotor test conditions of Caradonna, et al. and consist of parallel and oblique interactions. Comparison of the numerical results with test data show good agreement for both parallel and oblique interactions at subsonic and transonic tip speeds.

Srinivasan, G. R.↗

NASA NTRS1989

Evaluating local indirect addressing in SIMD proc essors

In the design of parallel computers, there exists a tradeoff between the number and power of individual processors. The single instruction stream, multiple data stream (SIMD) model of parallel computers lies at one extreme of the resulting spectrum. The available hardware resources are devoted to creating the largest possible number of processors, and consequently each individual processor must use the fewest possible resources. Disagreement exists as to whether SIMD processors should be able to generate addresses individually into their local data memory, or all processors should access the same address. The tradeoff is examined between the increased capability and the reduced number of processors that occurs in this single instruction stream, multiple, locally addressed, data (SIMLAD) model. Factors are assembled that affect this design choice, and the SIMLAD model is compared with the bare SIMD and the MIMD models.

Middleton, David↗

DOE OSTI2021

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Measurement of the 240 Pu(n,f) Prompt Fission Neutron Spectra with Chi-Nu

The DOE Nuclear Criticality Safety Program has funded a multi-year effort to measure the 240 Pu(n,f) Prompt Fission Neutron Spectrum at Chi-Nu. This project is a joint LANL-LLNL effort, involving the preparation of 12 240 Pu foils and construction of a Parallel-Plate Avalanche Counter at LLNL, with subsequent measurements of the 240 Pu(n,f) PFNS at the Chi-Nu beamline at the Los Alamos Neutron Science Center’s Weapons Neutron Research facility (LANSCE/WNR). We expect the PPAC to be ready in time to perform the measurements this run cycle.

240Pu Foils↗

NASA NTRSDate not supplied

Alternative Setup for Long-Duration Low-Duty-Cycle 600°C Ambient Testing of SiC Integrated Circuits

A scalable, compact oven testbed system for simultaneously evaluating a multitude of high temperature integrated circuits (ICs) for prolonged operating times of up to 600 °C has been prototyped. The new testbed system enables long-duration high temperature testing in sufficient statistical quantities consistent with standard aerospace electronics engineering standards. This setup is comprised of multiple compact ovens housing chips or packages mounted to ceramic circuit boards. Each oven is a compact 15.2 cm length by 15.2 cm width by 12.7 cm depth with a maximum 400 Watts of heating power. The custom-made silicon oxide ceramic heating block inside each oven is based on a 3D printed design adapted for the easy insertion of the IC device under test (DUT). This innovative design provides the quick insertion of ICs with or without a ceramic package into a 600 °C environment by utilizing a movable 11.43 cm long ceramic substrate with electrical traces extending from the oven hot zone to external standard plastic-based board connectors. Another key oven design feature is the minimization of the DUT exposure to electromagnetic interference (EMI) by utilizing a filtered DC power source to reduce heating element noise. Additionally, the ovens can be configured in a parallel arrangement allowing global data monitoring over a single industrial RS422 serial port. This feature is important for scaling up to test multiple ICs semi-simultaneously. A USB serial port is provided to independently control the operating parameters of each oven such as the oven target temperature and oven ramp rate. The oven temperature can reach up to 600 °C with a confirmed +/- 4 °C maximum deviation across the test zone region. The ramp rate can be programmed from 1 °C/minute up to 10 °C/minute. Furthermore, a programmable switchboard is used to interface with the DUT. This switchboard comprises a National Instruments Peripheral Component Interconnect eXtension for Instrumentation (NI PXI) system and a breakout board to send and receive power, analog or digital test signals. By using this unique oven testbed system, a variety of ICs can now be tested in parallel using the same test components configured for a diverse set of requirements.

DC Powered Oven↗

NASA NTRS1998

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. Unfortunately, an efficient parallel implementation is difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. To address this problem, we have developed PLUM, an automatic portable framework for performing adaptive large-scale numerical computations in a message-passing environment. First, we present an efficient parallel implementation of a tetrahedral mesh adaption scheme. Extremely promising parallel performance is achieved for various refinement and coarsening strategies on a realistic-sized domain. Next we describe PLUM, a novel method for dynamically balancing the processor workloads in adaptive grid computations. This research includes interfacing the parallel mesh adaption procedure based on actual flow solutions to a data remapping module, and incorporating an efficient parallel mesh repartitioner. A significant runtime improvement is achieved by observing that data movement for a refinement step should be performed after the edge-marking phase but before the actual subdivision. We also present optimal and heuristic remapping cost metrics that can accurately predict the total overhead for data redistribution. Several experiments are performed to verify the effectiveness of PLUM on sequences of dynamically adapted unstructured grids. Portability is demonstrated by presenting results on the two vastly different architectures of the SP2 and the Origin2OOO. Additionally, we evaluate the performance of five state-of-the-art partitioning algorithms that can be used within PLUM. It is shown that for certain classes of unsteady adaption, globally repartitioning the computational mesh produces higher quality results than diffusive repartitioning schemes. We also demonstrate that a coarse starting mesh produces high quality load balancing, at a fraction of the cost required a fine initial mesh. Results indicate that our parallel load balancing strategy will remain viable on large numbers of processors.

Oliker, Leonid↗

DOE OSTI2019

A Scalable Hybrid Scheme for Ray-Casting of Unstructured Volume Data

We present an algorithm for parallel volume rendering that is a hybrid between classical object order and image order techniques. The algorithm operates on unstructured grids (and structured ones), and thus can deal with block boundaries interleaving in complex ways. It also deals effectively with cases that are prone to load imbalance, i.e., cases where cell sizes differ dramatically, either because of the nature of the input data, or because of the effects of the camera transformation. The algorithm divides work over resources such that each phase of its processing is bounded in the amount of computation it can perform. We demonstrate its efficacy through a series of studies, varying over camera position, data set size, transfer function, image size, and processor count. At its biggest, our experiments scaled up to 8,192 processors and operated on data sets with more than one billion cells. In total, we find that our hybrid algorithm performs well in all cases. This is because our algorithm naturally adapts its computation based on workload, and can operate like either an object order technique or an image order technique in scenarios where those techniques are efficient.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗

DOE OSTI2016

Asynchronous in situ connected-components analysis for complex fluid flows

Fluid flow in porous media is at the heart of problems such as groundwater contamination and carbon sequestration, and presents an important challenge for scientific computing. For this class of problem, large three-dimensional simulations are performed to advance scientific inquiry. On massively parallel computing systems, the volume of data generated by such approaches can become a productivity bottleneck if the raw data generated from the simulation is analyzed in a post-processing step. We present a physics-based framework for in situ data reduction that is theoretically grounded in multiscale averaging theory. We show how task parallelism can be exploited to concurrently perform a variety of analysis tasks with data-dependent costs, including the generation of iso-surfaces, morphological analyses, and connected components analysis. A task management framework is constructed to launch asynchronous analysis threads, manage dependencies between different tasks, promote data locality and hide the impact of data transfers. The framework is applied to analyze GPU-based simulations of two-fluid flow in porous media, generating a set of averaged measures that represents the overall system behavior. We demonstrate how the approach can be applied to perform physically-consistent averaging over fluid subregions using connected components analysis. Simulations performed on Oak Ridge National Lab s Titan supercomputer are profiled to demonstrate the performance of the associated multi-threaded in situ analysis for typical production simulation of two-fluid flow.

Mcclure, James↗